To assess whether the patient's self-reported pain level is associated with a multivariate physiological biomarker bias achieved in the actual clinical setting. This study will use a clinical-grade wearable sensor to continuously monitor the patient's physiological condition (pain-related biomarkers) and use the mobile app to allow participants to actively report their pain scores, symptoms and quality of life.After analysis of the biomarkers we may predict the coming pain attacks by way of the meaningful biomarkers.

Subjective scores have traditionally been used to measure human pain, such as the visual analog scale (VAS) to determine the presence or absence of pain and its severity. People can only express the pain experienced by dictation, scale, and image depicting the degree of pain. Although this is important information, the self-evaluation method has problems for diagnosis and research purposes. The results of a person's self-assessment depend on past pain experiences and many other cognitive and behavioral factors and therefore change over time. In addition, it is difficult to obtain a reliable comparison between the rewards of different people. When the patient complains of a certain degree of pain, it is impossible to know whether it is equivalent to the same pain described by other patients. Moreover, it is difficult to obtain self-evaluation results among ethnic groups of different natures, such as young people, patients who block the transmission of ideas due to different disease types, and those who are unconscious. A variety of survey-based pain scales and functions have been developed recently, and the utility has improved.

However, because it is still based on self-assessment, it will leave some of the same problems with self-assessment. Developmental measurements of biomarkers or surrogate markers with acute and/or chronic pain have made significant progress over the past few years. Thanks to the development of new and improved technologies, such as in the field of angiography and wearable biosensors, there has been considerable development. Studies have shown that pupils respond to a variety of different stimuli and may predict the presence of pain. There are many different physiological parameters, such as changes in heart rate, pulsating components of the heart cycle, and skin activity, which have been shown to be associated with the presence or absence of pain. From the development of research in this field, it is feasible to develop clinical tools for measuring the presence or absence of acute and/or chronic pain, including cancer pain, using biomarkers or surrogate markers. This objective tool can make more significant advances in clinical pain research and treatment.

Inclusion Criteria:

There are moderate to severe cancer pain (digital rating scale NRS ≥ 4).

Inclusion conditions:

1. Male and female between the ages of 21 and 70
2. Cancer patients diagnosed with moderate to severe cancer pain (digital rating scale NRS ≥ 4)
3. Ability to provide informed consent
4. Be able to commit to using the app during the study and input data as needed
5. The subject must have a smart phone such as an iPhone/iPad (at least iPhone 5S)

Exclusion Criteria:

1. Previously had myocardial infarction (MI)
2. Coronary artery disease is known - previous coronary angioplasty
3. A previous stroke occurred, and stroke was defined as a new localized nerve defect lasting more than 24 hours.
4. Currently using more than 2 kinds of blood pressure lowering drugs
5. Expected life is less than 1 year
6. Suffering from asthma or chronic lung disease requires long-term medication or oxygen therapy
7. suffering from mental illness, the clinical judgment of the host will affect the participation of the trial, such as dementia
8. Unable to comply with the test plan
9. Any other acute or chronic medical/physiological condition identified by the moderator as affecting the test results

There are moderate to severe cancer pain (digital rating scale NRS ≥ 4).